Colorimetric sensor array based on gold nanoparticles: Design principles and recent advances

Green and sustainable smart wooden system integrated with cellulose nanowhiskers-supported polyvinyl alcohol and anthocyanin biomolecules to monitor food freshness

Smart packaging materials have been used to protect human health from environmental hazards by sending real-time colorimetric signals for changes in the food packaging environment. However, the colorimetric material sensors use synthetic sensor dyes, which are toxic, expensive, non-biodegradable, and difficult to prepare. Herein, a simple strategy is presented for the development of an environmentally-friendly halochromic wood able to change color upon exposure to spoilage of food. A combination of anthocyanin (Ac)/aluminum (Al) mordant (Ac/Al) nanoparticles and cellulose nanowhiskers (CNW)-reinforced polyvinyl alcohol (PVA) was infiltrated into a delignified wood to produce a translucent wood with halochromic properties. CNW were employed as reinforcement agent to improve the mechanical performance of PVA. Additionally, CNW function as a dispersing agent to prevent agglomeration of Ac/Al nanoparticles. The diameters of CNW are in the range of 12-19 nm, whereas Ac/Al particles showed diameters of 9-22 nm. The smart wood changed color from purplish to colorless when exposed to food spoilage. A hypsochromic change from 539 nm to 370 nm was shown by the anthocyanin receptor when the spoilage level of food increased. This could be attributed to the pH-driven molecular switching of anthocyanin, leading to charge delocalization.

Recent advances and synergistic effect of bioactive zeolite imidazolate frameworks (ZIFs) for biosensing applications

The rapid developments in the field of zeolitic imidazolate frameworks (ZIFs) in recent years have created unparalleled opportunities for the development of unique bioactive ZIFs for a range of biosensor applications. Integrating bioactive molecules such as DNA, aptamers, and antibodies into ZIFs to create bioactive ZIF composites has attracted great interest. Bioactive ZIF composites have been developed that combine the multiple functions of bioactive molecules with the superior chemical and physical properties of ZIFs. This review thoroughly summarizes the ZIFs as well as the novel strategies for incorporating bioactive molecules into ZIFs. They are used in many different applications, especially in biosensors. Finally, biosensor applications of bioactive ZIFs were investigated in optical (fluorescence and colorimetric) and electrochemical (amperometric, conductometric, and impedance) fields. The surface of ZIFs makes it easier to immobilize bioactive molecules like DNA, enzymes, or antibodies, which in turn enables the construction of cutting-edge, futuristic biosensors.

Paper-based optical sensor arrays for simultaneous detection of multi-targets in aqueous media: A review

Sensor arrays, which draw inspiration from the mammalian olfactory system, are fundamental concepts in high-throughput analysis based on pattern recognition. Although numerous optical sensor arrays for various targets in aqueous media have demonstrated their diverse applications in a wide range of research fields, practical device platforms for on-site analysis have not been satisfactorily established. The significant limitations of these sensor arrays lie in their solution-based platforms, which require stationary spectrophotometers to record the optical responses in chemical sensing. To address this, this review focuses on paper substrates as device components for solid-state sensor arrays. Paper-based sensor arrays (PSADs) embedded with multiple detection sites having cross-reactivity allow rapid and simultaneous chemical sensing using portable recording apparatuses and powerful data-processing techniques. The applicability of office printing technologies has promoted the realization of PSADs in real-world scenarios, including environmental monitoring, healthcare diagnostics, food safety, and other relevant fields. In this review, we discuss the methodologies of device fabrication and imaging analysis technologies for pattern recognition-driven chemical sensing in aqueous media.

Accurately recognizing chromium species with multi-functionalized nano Au-based sensor array

High-resolution identification of chromium (Cr) species, especially various organic-Cr complexes, in a convenient and economically-feasible manner is the prerequisite for achieving the advanced treatment of chromium wastewater. To this end, a colorimetric nano-Au sensor array was developed by taking advantage of the UV-spectra shift of gold nanoparticles (Au NPs) upon interaction with Cr species; specifically, four molecular modifiers [i.e., iminodiacetic acid (IDA), tripolyphosphate (TPP), cetyltrimethylammonium bromide (CTAB), and 1,5-diphenylcarbazide (DPC)] were intentionally employed for assembling nano-Au array receptors, which showed respective responses toward different Cr species through the formation of coordination, hydrophobic interaction, electrostatic attraction, and redox reaction, respectively; the "fingerprint" differences of the unique optical properties were then integrated for semi-quantitatively recognizing Cr species by pattern recognition techniques. Eleven ubiquitous Cr species [i.e., Cr(III), Cr(VI), and various Cr(III)-organic complexes] served as the model samples, which could be sensitively identified, no matter in individual or mixture mode, by the developed nano-Au sensor array on the basis of the colorimetric responses resulted from diverse nano-Au-aggregation behaviors, with excellent anti-interference ability in the simulated or actual water scenario. Attractively, the nano-Au sensor array can achieve very sensitive detection limit of the quantitative analyses of Cr species in a prompt in-situ manner, which usually requires a two-step process of separation and detection for the conventional analytical methods. Such a convenient strategy of Cr species discrimination conduces to rationally designing specific protocols for the advanced treatment of chromium wastewater.

Enhanced detection of acetamiprid via a gold nanoparticle-based colorimetric aptasensor integrated with a hybridization chain reaction

This study presents a novel colorimetric aptasensor, which seamlessly integrates gold nanoparticles (AuNPs) with the amplification potential of the hybridization chain reaction (HCR) for enhanced detection of acetamiprid. The aptamer, hybridized with a partially complementary strand that is covalently linked to AuNPs, serves as the recognition element for acetamiprid. The free end sequence of the aptamer, distal from the AuNP surface, functions as the initiating strand for the HCR, triggering the amplification process. In the absence of acetamiprid, the HCR efficiently occurs, conferring robust salt tolerance to the AuNPs and maintaining their characteristic red coloration. However, in the presence of acetamiprid, the aptamer preferentially binds to its target, disrupting the double-stranded structure and leading to the dissociation of the aptamer from the AuNPs. This dissociation results in a decrease in the HCR product, subsequently diminishing the salt tolerance of AuNPs and triggering a colorimetric transition from red to gray. This integration enhances sensitivity to 3.14 nM. Additionally, carbon quantum dots (CQDs) transduce colorimetric signals to fluorescent ones, further boosting the sensitivity to 0.24 nM. The aptasensor exhibits excellent selectivity and robustness. Real-world testing on tomato, peach, and lettuce shows recoveries of 98.50% to 100.36% with low standard deviations, validating its utility for pesticide residue analysis and food safety. This study provides a powerful tool for rapid and accurate pesticide detection, crucial for food safety.

A fluorescent sensor array based on a single cucurbit[5]uril-truxene probe for simultaneous identification of five heavy metal ions

There is a need to develop simple and effective strategies for the rapid detection of heavy metal ions (HMIs) in order to protect the environment and human health. A simple fluorescent sensor array based on a single cucurbit[5]uril-truxene probe was proposed to simultaneously identify five HMIs (Pb2+, Cu2+, Ag+, Fe2+ and Fe3+). This probe was synthesized using monohydroxyl cucurbit[5]uril and monobromohexyl truxene by a substitution reaction between them. It could be observed that the fluorescence response of this synthesized probe to HMIs was closely related to the pH of the aqueous solution, exhibiting different fluorescence intensities at pH 3.0, 7.0, and 9.0. Based on this phenomenon, a fluorescent sensor array based on a single cucurbit[5]uril-truxene probe was then constructed by simply altering the pH in the sensor element. These unique fluorescence responses were analyzed using linear discriminant analysis (LDA) to identify metal ions. A concentration limit classification of 0.1 μM was applied to the above five HMIs. Moreover, the quantification of metal ions was implemented even at low concentrations of 48-121 nM. This array showed good results in the recognition of metal ions in real water samples (lake water and tap water samples), which shows its broad application prospects in many fields, including monitoring of the environmental water quality and so on.

Au nanozyme-based colorimetric sensor array integrates machine learning to identify and discriminate monosaccharides

As different monosaccharides exhibit different redox characteristics, this paper presented a novel colorimetric sensor array based on the glucose oxidase-like (GOx-like) activity of Au nanoparticles (NPs) for monosaccharides identification. AuNPs can use O2, ABTS+•, or [Ag(NH3)2]+ as an electron acceptor to catalyze the oxidation of monosaccharides in different velocity, resulting in cross-responsive signals. The current sensor array can distinguish between different monosaccharides or their mixtures through linear discriminant analysis (LDA) and hierarchical clustering analysis (HCA). Moreover, the glucose and fructose concentrations can be estimated simultaneously using a neural network regression model based on the sensor array. This method shows potential for monosaccharide detection in industrial, medical, and biological applications.

Machine learning-assisted chromium speciation using a single-well ratiometric fluorescent nanoprobe

Chromium is widely recognized as a significant pollutant discharged into the environment by various industrial activities. The toxicity of this element is dependent on its oxidation state, making speciation analysis crucial for monitoring the quality of environmental water and assessing the potential risks associated with industrial waste. This study introduces a single-well fluorometric sensor that utilizes orange emissive thioglycolic acid stabilized CdTe quantum dots (TGA-QDs) and blue emissive carbon dots (CDs) to detect and differentiate between various chromium species, such as Cr (III) and Cr (VI) (i.e., CrO42- and Cr2O72-). The variations of fluorescence spectra of the proposed probe upon chromium species addition were analyzed using machine learning techniques such as linear discriminant analysis and partial least squares regression as a classification and multivariate calibration technique, respectively. Linear discriminant analysis (LDA) demonstrated exceptional accuracy in differentiating single-component and bicomponent samples. Additionally, the findings from the partial least squares regression (PLSR) showed that the sensor created has strong linearity within the 1.0-100.0, 1.0-100.0, and 0.1-15 μM range for Cr2O72-, CrO42-, and Cr3+, respectively. Furthermore, appropriate detection limits were successfully achieved, which were 2.6, 2.9, and 0.7 μM for Cr2O72-, CrO42-, and Cr3+, respectively. Ultimately, the successful capability of the sensing platform in the identification and quantification of chromium species in environmental water samples provides innovative insights into general speciation analytics.

Detection of Volatile Organic Compounds through Spectroscopic Signatures in Nanoporous Fabry-Pérot Optical Microcavities

Increasingly complex modern gas-monitoring scenarios necessitate advanced sensing capabilities to detect and identify a diverse range of gases under varying conditions. There is a rising demand for individual sensors with multiple responses capable of recognizing gases, identifying components in mixtures, and providing stable responses. Inspired by gas sensors employing multivariable response principles, we develop a nanoporous anodic alumina high-order microcavity (NAA-HOμCV) gas sensor with multiple optical outputs for discriminative gas detection. The NAA-HOμCV architecture, formed by a Fabry-Pérot microcavity with distributed Bragg reflector (DBR) mirrors and an extended-length microcavity layer supporting multiple resonant modes, serves as an effective solid-state fingerprint platform for distinguishing volatile organic compound (VOC) gases. Our research reveals that the coupling strength of light into resonant modes and their evolution depend on the thickness of the DBR mirrors and the dimension of the microcavity layer, which allows us to optimize the discriminative sensing capability of the NAA-HOμCV sensor through structural engineering of the microcavity and photonic crystal mirrors. Gas-sensing experiments conducted on the NAA-HOμCV sensor demonstrate real-time discrimination between physiosorbed VOC gases (isopropanol, ethanol, or acetone) in reversible gas sensing. It also achieves superior ppb-level sensing in irreversible gas sensing of model silane molecules. Our study presents promising avenues for designing compact, cost-effective, and highly efficient gas sensors with tailored properties for discriminative gas detection.

Hydrogen Bonding-Induced Aggregation of Chiral Functionalized AuNS@Ag NPs for Photothermal Enantioanalysis

Toward the challenges of signaling transduction amplified in enantioselective recognition, we herein devised an innovative strategy for highly selective recognition of amino acids and their derivatives, leveraging photothermal effects. In this approach, bifunctional l-ascorbic acid is employed to reduce silver ions in situ on Au nanostars. Simultaneously, its oxidate (l-dehydroascorbic acid) is bonded to the silver shell as a chiral selector to prepare chiral nanoparticles (C-AuNS@Ag NPs) with the ability to recognize stereoisomers and sensitively modulate the photothermal effect. l-Dehydroascorbic acid can selectively capture one of the enantiomers of the two forms through hydrogen bonding and drive aggregation of the nanoparticles, which sharply enhances the photothermal effect. Consequently, the two forms of the system exhibit a significant temperature difference, which enables the discrimination and quantification of enantiomers. Our strategy verifies that six chiral amino acids and their derivatives can be discriminated with enantioselective response values of up to 79. Additionally, the chiral recognition mechanism was revealed through density functional theory (DFT) calculations, providing a paradigm shift in the development of enantiomeric recognition strategies.

Colorimetric sensor array for versatile detection and discrimination of model analytes with environmental relevance

In the current work, a rapid, simple, low-cost, and sensitive smartphone-based colorimetric sensor array coupled with pattern-recognition methods was proposed for the determination and differentiation of some organic and inorganic bases (i.e., OH-, CO32-, PO43-, NH3, ClO-, diethanolamine, triethanolamine) as model compounds. The sensing system has been designed based on color-sensitive dyes (Fuchsine, Giemsa, Thionine, and CoCl2) which were used as sensor elements. The color changes of a sensor array were observed by the naked eye. The color patterns were recorded using digital imaging in a three-dimensional (red, green, and blue) space and quantitatively analyzed with color calibration techniques. Distinctive colorimetric patterns for target bases via linear discriminant analysis (LDA) and hierarchical clustering analysis (HCA) were observed. The results indicated that the analytes related to each class (at the different concentration levels in the range of 0.001-1.0 mol L-1) were clustered together in the canonical discriminant plot and HCA dendrogram with high sensitivity and an overall precision of 85%. Furthermore, the first function factor of LDA correlated with the concentration of each target analyte in a correlation coefficient (R2) range of 0.864-0.996. These described procedures based on the colorimetric sensor array technique could be a promising candidate for practical applications in package technology and facile detection of pollutants.

Fabrication of paper-based analytical devices using stencil-printed glass varnish barriers for colorimetric detection of salivary α-amylase

BACKGROUND

Developing disposable paper-based devices has positively impacted analytical science, particularly in developing countries. Some benefits of those devices include their versatility, affordability, environmentally friendly, and the possibility of being integrated with portable electrochemical or colorimetric detectors. Paper-based analytical devices (PADs) comprising circular zones and microfluidic networks have been successfully employed in the analytical chemistry reign. However, the combination of the stencil-printing method and alternative binder has not been satisfactorily explored for fabricating colorimetric paper devices.

RESULTS

We developed PADs exploring the stencil printing approach and glass varnish as the hydrophobic chemical agent. As a proof-of-concept, the colorimetric assay of salivary α-amylase (sAA) was performed in saliva samples. Through the scanning electron microscopy measurements, it was possible to indicate satisfactory definitions between native fibers and barrier, and that the measured values for the channel width revealed suitable fidelity (R2 = 0.99) with the nominal widths (ranging from 400 to 5000 μm). The proposed hydrophobic barrier exhibited excellent chemical resistance. The analytical applicability for detecting sAA revealed linear behavior in the range from 2 to 12 U mL-1 (R2 = 0.99), limit of detection of 0.75 U mL-1, reproducibility (RSD ≤2.4%), recovery experiments ranged from 89 to 108% and AGREE response (0.86). In addition, the colorimetric analysis of sAA in four different saliva samples demonstrated levels ranging from 202 to 2080 U mL-1, which enabled monitoring the absence and presence of periodontitis.

SIGNIFICANCE

This report has presented the first use of a self-adhesive mask and glass varnish for creating circular zones and microfluidic architectures on paper without using thermic or UV curing treatments. Also, the proposed analytical methodology for detecting sAA exhibited suitable ecological impact considering the AGREE tool. We believe the proposed fabrication of paper devices emerges as a novel, simple, high-fidelity microfluidic channel and portable analytical approach for colorimetric sensing.

Development of Optical Differential Sensing Based on Nanomaterials for Biological Analysis

The discrimination and recognition of biological targets, such as proteins, cells, and bacteria, are of utmost importance in various fields of biological research and production. These include areas like biological medicine, clinical diagnosis, and microbiology analysis. In order to efficiently and cost-effectively identify a specific target from a wide range of possibilities, researchers have developed a technique called differential sensing. Unlike traditional "lock-and-key" sensors that rely on specific interactions between receptors and analytes, differential sensing makes use of cross-reactive receptors. These sensors offer less specificity but can cross-react with a wide range of analytes to produce a large amount of data. Many pattern recognition strategies have been developed and have shown promising results in identifying complex analytes. To create advanced sensor arrays for higher analysis efficiency and larger recognizing range, various nanomaterials have been utilized as sensing probes. These nanomaterials possess distinct molecular affinities, optical/electrical properties, and biological compatibility, and are conveniently functionalized. In this review, our focus is on recently reported optical sensor arrays that utilize nanomaterials to discriminate bioanalytes, including proteins, cells, and bacteria.

Facile Synthesis of PEGylated Gold Nanoparticles for Enhanced Colorimetric Detection of Histamine

Histamine is among the biogenic amines that are formed during the microbial decarboxylation of amino acids in various food products, posing a significant threat to both food safety and human health. Herein, we present a one-step synthesis of PEGylated gold nanoparticles (PEG-AuNPs) for rapid, simple, and cost-effective colorimetric histamine detection. PEG-AuNPs' surface plasmon resonance (SPR) range at 520-530 nm with a hydrodynamic size distribution of 20-40 nm. Fourier transform infrared (FT-IR) spectra confirmed the reduction of AuNPs at 1645 cm-1 along with the other observed peaks at 2870, 1350, and 1100 cm-1 as a strong evidence for the presence of PEG. Upon the addition of histamine to the PEG-AuNP solution, transmission electron microscopy (TEM) highlighted the aggregation of nanoparticles. In addition, red shifting and a decrease in the absorbance of the SPR peak along with the appearance of an additional peak at ∼690 nm was observed in the PEG-AuNP absorption spectra in the presence of histamine. Increasing the PEG concentration in the gold colloids leads to the formation of a protective barrier around the surface of nanoparticles, which influences the colloidal stability by impeding the aggregation of PEG-AuNPs upon histamine addition. The minimum colorimetric response of PEG-AuNPs to histamine concentration is 30 ppm, as assessed by the naked eye. The absorption ratio (A690/A526) showed a linear dynamic range from 20 to 100 ppm with a limit of detection of 9.357 μM. Additionally, the assay demonstrates a commendable selectivity toward histamine analyte.

Surveillance of pathogenic bacteria on a food matrix using machine-learning-enabled paper chromogenic arrays

Global food systems can benefit significantly from continuous monitoring of microbial food safety, a task for which tedious operations, destructive sampling, and the inability to monitor multiple pathogens remain challenging. This study reports significant improvements to a paper chromogenic array sensor - machine learning (PCA-ML) methodology sensing concentrations of volatile organic compounds (VOCs) emitted on a species-specific basis by pathogens by streamlining dye selection, sensor fabrication, database construction, and machine learning and validation. This approach enables noncontact, time-dependent, simultaneous monitoring of multiple pathogens (Listeria monocytogenes, Salmonella, and E. coli O157:H7) at levels as low as 1 log CFU/g with over 90% accuracy. The report provides theoretical and practical frameworks demonstrating that chromogenic response, including limits of detection, depends on time integrals of VOC concentrations. The paper also discusses the potential for implementing PCA-ML in the food supply chain for different food matrices and pathogens, with species- and strain-specific identification.

Gold nanobipyramid colorimetric sensing array for the differentiation of strong aroma-type baijiu with different geographical origins

It is of great significance to quickly and effectively distinguish strong aroma-type baijiu (SAB) with the largest baijiu market share and the most extensive production regions. Colorimetric sensor arrays based on gold nanobipyramids (AuNBPs) with extraordinary plasmonic properties were constructed for the differentiation of SAB from different geographical origins. The sensing strategy was based on silver deposition on different morphologies of AuNBPs under different reducing conditions containing amino or hydroxyl groups. The deposition process can be effective for distinguishing differences in baijiu due to the chemical interaction between the trace ingredients in baijiu and reductants. The colorimetric sensor arrays were implemented for the response of the main ingredients and further used for the differentiation of SAB from different regions by linear discriminant analysis. The results showed that the sensing strategy had excellent performance in distinguishing SAB from different origins, and provides a promising application strategy for baijiu quality control.

Triple-Emission Single Sensing Element-Enabled Ratiometric Fluorescent Array Identification of Multiple Antibiotics

Given that intricate toxicological profiles exist among different antibiotics and pose serious threats to the environment and human health, synchronous analysis of multiple residues becomes crucial. Sensor arrays show potential to achieve the above purpose, but it is challenging to develop easy-to-use and high-sensitivity tools because the state-of-the-art arrays often require more than one recognition unit and are monosignal dependent. Here we exquisitely designed a fluorescent nanoprobe (2-aminoterephthalic acid-anchored CdTe quantum dots with Eu3+ coordination, CdTe-ATPA-Eu3+) featuring triple emissions at the same excitation as the only element to fabricate a luminescent sensor array with ratiometric calculations for identifying multiple antibiotics. By taking tetracycline, chlortetracycline, doxycycline, oxytetracycline, penicillin G, and sulfamethoxazole as models, the six species exhibited distinguishable motivation or/and quenching impacts on the three emissions of CdTe-ATPA-Eu3+, which were employed as indicators to perform the ratiometric logical operation and further combined with pattern recognition analysis for multitarget determination. Evidently, such a design exhibits two advances: (1) with the triple-emission probe as the sole receptor requiring neither internal nor external adjustments, the fabricated array acts as an extremely facile tool for multianalyte detection; (2) the ratiometric calculations offer excellent sensitivity and reliability for high-performance determination. Consequently, accurate identification and quantification of individual antibiotics and their combinations at various levels were verified in both laboratory and practical matrices. Our work provides a new tool for simultaneously detecting multiple antibiotics, and it will inspire the development of advanced sensor arrays for multitarget analysis.

Smartphone-assisted nanozyme sensor array constructed based on reaction kinetics for the discrimination and identification of phenolic compounds

Although the research on nanozymes has attracted widespread attention in recent years, the development of highly active and multifunctional nanozymes remains a challenge. Here, a bifunctional AMP-Cu nanozyme with laccase- and catecholase-like activities was successfully prepared at room temperature with Cu2+ as the metal ion and adenosine-5'-monophosphate (AMP) as the ligand molecule. Based on the excellent catalytic performance of AMP-Cu, a three-channel colorimetric sensor array was constructed using reaction kinetics as the sensing unit to achieve high-throughput detection and identification of six common phenolic compounds at low concentrations. This strategy simplifies the construction of sensor array and demonstrates the capacity to obtain multidimensional data from a single material. Finally, with the assistance of smartphones and homemade dark boxes, a portable on-site detection method for phenolic compounds was developed. This work would contribute to the development of portable sensors and the highly efficient identification of phenolic compounds in complex samples.

Quantum dots-based "chemical tongue" for the discrimination of short-length Aβ peptides

A "chemical tongue" is proposed based on thiomalic acid-capped quantum dots (QDs) with signal enrichment provided by excitation-emission matrix (EEM) fluorescence spectroscopy for the determination of close structural analogs-short-length amyloid β (Aβ) peptides related to Alzheimer's disease. Excellent discrimination is obtained by principal component analysis (PCA) for seven derivatives: Aβ1-16, Aβ4-16, Aβ4-9, Aβ5-16, Aβ5-12, Aβ5-9, Aβ12-16. Detection of Aβ4-16, Aβ4-16, and Aβ5-9 in binary and ternary mixtures performed by QDs-based chemical tongue using partial least squares-discriminant analysis (PLS-DA) provided perfect 100% accuracy for the two studied peptides (Aβ4-16 and Aβ4-16), while for the third one (Aβ5-9) it was slightly lower (97.9%). Successful detection of Aβ4-16 at 1 pmol/mL (1.6 ng/mL) suggests that the detection limit of the proposed method for short-length Aβ peptides can span nanomolar concentrations. This result is highly promising for the development of simple and efficient methods for sequence recognition in short-length peptides and better understanding of mechanisms at the QD-analyte interface.

Different sized gold nanoparticles for array-based sensing of pesticides and its application for strawberry pollution monitoring

The use of pesticides plays an essential role in improving crop quality and yield, however, it causes air, water, and soil pollution and the residue of these pesticides in agricultural products threatens the ecosystem and human life. Therefore, it is highly desirable to develop rapid, simple, and cost-effective methods for regular monitoring of pesticide residues in agricultural products especially strawberry that is consumed fresh and unpeeled. In this study, gold nanoparticles (AuNPs) of varying sizes have been exploited as sensing units to design a non-enzymatic colorimetric sensor array for the detection and discrimination of various pesticides including; bifenazate (BF), paraquat (PQ), diazinon (DZ), thiometon (TM), and carbendazim (CD) and chlorpyrifos (CP). Because of their strong size- and environmentally-dependent properties, AuNPs with different sizes produced distinguished plasmonic patterns in the presence of pesticides at a vast range of concentrations (25-800 ng mL-1). Plasmonic patterns of sensor units have been analyzed by various data visualization (bar plots and heat maps) and pattern recognition methods (linear discriminant analysis (LDA)). The multivariate calibrations showed linear responses ranging from 50 to 800 ng mL-1 for carbendazim, chlorpyrifos, paraquat, and bifenazate and 25-800 ng mL-1 for diazinon and thiometon. The limit of detection (LOD) was calculated to be 17.7, 22.8, 22.4, 9.7, 7.4, and 23.8 ng mL-1 for carbendazim, chlorpyrifos, paraquat, diazinon, thiometon, and bifenazate respectively. Finally, the applicability of the designed sensor was evaluated in real samples comprising tap water, well water, soil, and fruit, leave, drainage water, and culture substrate of strawberry.

Smartphone-assisted quantitative colorimetric identification of thrombin based on peroxidase mimetic features of fibrinogen-gold nanozymes

Fibrinogen-modified gold nanoparticles (Fib-AuNPs) and 3,3',5,5'-tetramethylbenzidine (TMB) substrate besides hydrogen peroxide (H2O2) were applied for assessment of the biomarker thrombin. Fib-AuNPs have catalytic active sites for the oxidation of TMB besides H2O2 and cause the color change of the substrate. Moreover, they can lead to the enhancement in the absorption wavelengths of 650 and 370 nm. By the addition of thrombin to Fib-AuNPs, fibrinogen turns into fibrin, and AuNPs are surrounded by fibrin. Therefore, their active catalytic sites for the oxidation of TMB besides H2O2 are covered by fibrin and cannot cause color change and absorption increase as before. The relationship between the average variations of the color intensity and changes in the absorption wavelengths at 650 and 350 nm with different concentrations of bovine thrombin added to Fib-AuNPs was studied. In such manner, three sensitive colorimetric approaches have been developed for the identification of bovine thrombin with the linear range of 20-120 pM and the limit of detection (LOD) of 17.54 pM for the average color intensity (G + B), the linear range of 20-120 pM and the LOD of 13.41 pM for the absorption peak at 650 nm, and the linear range of 40-140 pM with the LOD of 18.85 pM for absorption peak at 370 nm. The practical application of this biosensing platform was indicated through the successful determination of bovine thrombin in bovine serum. The satisfactory RSD ( < 10%) and recovery values (99.11-107.61%) confirmed the feasibility of the fabricated sensor.

Machine learning-assisted photoluminescent sensor array based on gold nanoclusters for the discrimination of antibiotics with test paper

Antibiotic residues accumulation in the environment endangers ecosystems and human health. There is an urgent need for a facile and efficient strategy to detect antibiotics. Here, we report a photoluminescent sensor array based on protein-stabilized gold nanoclusters (AuNCs) for the detection of two families of antibiotics, tetracyclines and quinolones. The nanoclusters were synthesized with bovine serum albumin (BSA) and ovalbumin (OVA), respectively. They had different interactions with seven kinds of antibiotics and exhibited diverse photoluminescence (PL) responses, which were analyzed by linear discriminant analysis and ExtraTrees algorithms. The sensor array performed well in both classification and quantification of seven antibiotics. And the quantitative results of all antibiotics obtained R2 of no less than 0.99 at 0-100 μM when using suitable regression models. Additionally, the sensor array was able to distinguish antibiotic mixtures and multiple interfering substances, and it also kept 100% classification accuracy in river water samples. Moreover, test paper assisted by a smartphone was applied for quick detection of antibiotics, with good performance in both HEPES buffer and river water. These studies reveal great potential for the point-of-use analysis of antibiotics in environmental monitoring.

Low-Cost Plant-Based Metal and Metal Oxide Nanoparticle Synthesis and Their Use in Optical and Electrochemical (Bio)Sensors

Technological progress has led to the development of analytical tools that promise a huge socio-economic impact on our daily lives and an improved quality of life for all. The use of plant extract synthesized nanoparticles in the development and fabrication of optical or electrochemical (bio)sensors presents major advantages. Besides their low-cost fabrication and scalability, these nanoparticles may have a dual role, serving as a transducer component and as a recognition element, the latter requiring their functionalization with specific components. Different approaches, such as surface modification techniques to facilitate precise biomolecule attachment, thereby augmenting recognition capabilities, or fine tuning functional groups on nanoparticle surfaces are preferred for ensuring stable biomolecule conjugation while preserving bioactivity. Size optimization, maximizing surface area, and tailored nanoparticle shapes increase the potential for robust interactions and enhance the transduction. This article specifically aims to illustrate the adaptability and effectiveness of these biosensing platforms in identifying precise biological targets along with their far-reaching implications across various domains, spanning healthcare diagnostics, environmental monitoring, and diverse bioanalytical fields. By exploring these applications, the article highlights the significance of prioritizing the use of natural resources for nanoparticle synthesis. This emphasis aligns with the worldwide goal of envisioning sustainable and customized biosensing solutions, emphasizing heightened sensitivity and selectivity.

An intelligent "chemical tongue" for high-order monitoring ATP-related physiological phosphates and ATP hydrolysis through diverse transduction principles

For discriminating diverse analytes and monitoring a specific chemical reaction, the emerging multi-channel "chemical nose/tongue" is challenging multi-material "chemical nose/tongue". The former contributes greatly to integrating different transduction principles from a single sensing material, avoiding the need for complex design, high cost, and tedious operation involved with the latter. Therefore, this high-order sensing puts a particular emphasis on the effects of encapsulation. Herein, the plasmonic gold nanoparticles (Au NPs) are encapsulated as a core into the fluorescent guanine monophosphate-Tb3+ infinite coordination polymer nanoparticles (GMP-Tb ICPs) to obtain a core-shell nanocomposite named Au NPs@GMP-Tb ICPs. Hence, a dual-channel "chemical tongue" based on Au NPs@GMP-Tb ICPs is present to realize high-order sensing of adenosine triphosphate (ATP)-related physiological phosphates and the monitoring of ATP hydrolysis. Considering the affinity of Tb3+ towards P-O bonds, four inorganic phosphates and three nucleotide phosphates with different phosphate group numbers and steric hindrance effect directly regulate two stimulus responses (fluorescence intensity and UV-vis absorbance) of Au NPs@GMP-Tb ICPs. Robust statistical methods, such as linear discriminant analysis and hierarchical cluster analysis, are used to recognize each phosphate by the developed sensor array either in the aqueous solution or in complex media such as serum, together with efficiently monitored ATP hydrolysis at different intervals. These findings and blind test clarify that the designed "chemical tongue" guarantees interference resistance and strengthens analytical capacity, together with offering valuable insight into "lab-on-a-nanoparticle" development for monitoring specific chemical reactions.

Smartphone-enabled colorimetric visual quantification of highly hazardous trivalent chromium ions in environmental waters and catalytic reduction of p-nitroaniline by thiol-functionalized gold nanoparticles

High-efficiency sensing systems for extremely hazardous chromium (Cr(III)) ions are important due to their detrimental effects on human health and the environment. We employed a spectrophotometric method combined with a smartphone (red, green, and blue (RGB) color ratio)-based detection platform to realize the quick, visually quantifiable in situ detection of Cr(III) ions using surface plasmon resonance (SPR)-aided colorimetry. For optical sensing nanoprobes, we synthesized the 2-Mercapto-5-methyl-1,3,4-thiadiazole (MMT)-modified gold nanoparticles (MMT-AuNPs) using a wet chemical method. By way of a coordination reaction, the Cr(III) ions induce the as-prepared MMT-AuNPs to aggregate and subsequently change the SPR wavelength band. The freshly synthesized MMT-AuNPs exhibited a wine-red color. While Cr(III) ions interact with the MMT-AuNPs, the color of the latter evolved from wine red to purple, thus facilitating visual monitoring. The SPR-relevant color change allowed the quantitative sensing of Cr(III) ions in the range of 40-128 nM, with the limit of detection of 6.93 nM when employing the spectrophotometric method and 12.4 nM when using the smartphone RGB color ratio. Furthermore, we developed the spectrophotometric technique that used the smartphone RGB color ratio for on-site analysis of Cr(III) ions in environmental water samples, indicating the possibility of its chemo-sensing applications for portable quantitative detection devices. Additionally, the catalytic performance of the MMT-AuNPs was demonstrated by the reduction of p-nitroaniline in the presence of sodium borohydride. It was interestingly unveiled that the MMT-AuNPs showed outstanding catalytic performance with a catalytic rate constant of 6.31 × 10-3 s-1.

Applications of Gas Sensing in Food Quality Detection: A Review

Food products often face the risk of spoilage during processing, storage, and transportation, necessitating the use of rapid and effective technologies for quality assessment. In recent years, gas sensors have gained prominence for their ability to swiftly and sensitively detect gases, making them valuable tools for food quality evaluation. The various gas sensor types, such as metal oxide (MOX), metal oxide semiconductor (MOS) gas sensors, surface acoustic wave (SAW) sensors, colorimetric sensors, and electrochemical sensors, each offer distinct advantages. They hold significant potential for practical applications in food quality monitoring. This review comprehensively covers the progress in gas sensor technology for food quality assessment, outlining their advantages, features, and principles. It also summarizes their applications in detecting volatile gases during the deterioration of aquatic products, meat products, fruit, and vegetables over the past decade. Furthermore, the integration of data analytics and artificial intelligence into gas sensor arrays is discussed, enhancing their adaptability and reliability in diverse food environments and improving food quality assessment efficiency. In conclusion, this paper addresses the multifaceted challenges faced by rapid gas sensor-based food quality detection technologies and suggests potential interdisciplinary solutions and directions.

Catechol oxidase nanozyme based colorimetric sensors array for highly selective distinction among multiple catecholamines

In order to effectively monitor multiple catecholamine (CA) neurotransmitters with extreme similar structures, a rapid, sensitive and selective detection strategy has become an urgent problem to be solved. In this paper, a novel colorimetric sensors array based on CuNCs protected by various ligands such as tannic acid, ascorbic acid and polymethylacrylic acid (CuNCs@TA, CuNCs@AA and CuNCs@PMAA) was constructed. All of these CuNCs could mimic catechol oxidase to selective catalyze catechol-type analogues (such as CAs) to corresponding quinones along with color changes. Furthermore, experiments and theory calculations demonstrated that Cr6+-modification on the surface of CuNCs facilitated the steady-state kinetics of enzymatic activity. Based on these CuNCs as sensing probes, this sensors array can quickly detect different CAs (such as epinephrine (EP), including dopamine (DA), norepinephrine (NE) and l-dopa) with similar structures. When those analogues were added to the CuNC-based colorimetric array sensors, different absorbance changes were produced at 485 nm. Linear discriminant analysis (LDA) showed that the tri-probe colorimetric array sensors could recognize and distinguish these analogues, and corresponding binary and ternary mixtures could be well categorized. The value of Factor 1 of an array with varied CA concentrations had a good linear correlation, and the detection limit (LOD) was as low as 10-8∼10-9 mol/L. Four CA analogues in real samples were identified by CuNCs-based colorimetric array sensors. This work provides a fast and convenient experimental basis for monitoring the complex structure CAs neurotransmitters.

Progress in optical sensors-based uric acid detection

The escalating number of patients affected by various diseases, such as gout, attributed to abnormal uric acid (UA) concentrations in body fluids, has underscored the need for rapid, efficient, highly sensitive, and stable UA detection methods and sensors. Optical sensors have garnered significant attention due to their simplicity, cost-effectiveness, and resistance to electromagnetic interference. Notably, research efforts have been directed towards UA on-site detection, enabling daily monitoring at home and facilitating rapid disease screening in the community. This review aims to systematically categorize and provide detailed descriptions of the notable achievements and emerging technologies in UA optical sensors over the past five years. The review highlights the advantages of each sensor while also identifying their limitations in on-site applications. Furthermore, recent progress in instrumentation and the application of UA on-site detection in body fluids is discussed, along with the existing challenges and prospects for future development. The review serves as an informative resource, offering technical insights and promising directions for future research in the design and application of on-site optical sensors for UA detection.

Cellulose acetate/MOF film-based colorimetric ammonia sensor for non-destructive remote monitoring of meat product spoilage

Herein, we designed an on-site and portable colorimetric assay using cellulose acetate polymeric films incorporated with HKUST-1 metal-organic framework while immersed in a solution of methyl red and brilliant cresyl blue organic dyes as an indicator for monitoring ammonia levels. Ammonia serves as a significant biomarker of food spoilage which falls under the category of volatile organic compounds (VOCs). The designed colorimetric solid-state sensor was comprehensively characterized using FE-SEM, EDS-mapping, XRD, FTIR, and contact angle analyses. The results confirmed the superior stability, water permeability, good crystallinity and desirable morphology of the prepared sensor platform. Additionally, customized smartphone was developed and applied for online signaling and colorimetric analysis. The findings demonstrated two linear ranges: 1-100 ppb and 0.1-1340 ppm with a detection limit of 0.02 ppm. The solid-state sensor exhibited high selectivity in the presence of other VOCs such as methanol, ethanol, acetone, 2-propanol, toluene, humidity, and hexane. It displayed acceptable repeatability in both inter-day (RSD = 3.38 %) and intraday (RSD = 3.86 %), long-term stability over 4 days as well as reusability over 3 cycles. We successfully applied this sensing platform for ammonia monitoring in spoiled meat foods including veal, fish and chicken. The results indicated favorable percentage recovery and repeatability, confirming the feasibility and potential applicability of this intelligent packaging system for monitoring freshness. The platform allows for real-time monitoring and data analysis via smartphone-based online signaling, providing a convenient and effective method for ensuring food quality.

Advanced Textile-Based Wearable Biosensors for Healthcare Monitoring

With the innovation of wearable technology and the rapid development of biosensors, wearable biosensors based on flexible textile materials have become a hot topic. Such textile-based wearable biosensors promote the development of health monitoring, motion detection and medical management, and they have become an important support tool for human healthcare monitoring. Textile-based wearable biosensors not only non-invasively monitor various physiological indicators of the human body in real time, but they also provide accurate feedback of individual health information. This review examines the recent research progress of fabric-based wearable biosensors. Moreover, materials, detection principles and fabrication methods for textile-based wearable biosensors are introduced. In addition, the applications of biosensors in monitoring vital signs and detecting body fluids are also presented. Finally, we also discuss several challenges faced by textile-based wearable biosensors and the direction of future development.

Diazo-reaction based dual-mode colorimetric-electrochemical sensing of nitrite in pickled food

Development of an effective and convenient sensor for sensitive detection of nitrites is of great concern since excessive amounts of nitrites can be harmful to both human health and the environment. In this work, Cu-MOF modified exfoliated graphite paper (EGP) was employed as a signal reporter to enable the visual and electrochemical dual-mode sensing of nitrites. Cu-MOFs were in situ synthesized on EGP, which exhibited an excellent oxidase enzyme-like activity to oxidize 3,3',5,5'-tetramethylbenzidine (TMB) into its oxidation product (oxTMB). The multi-layer structure and the superior electrical conductivity of EGP not only facilitated the loading of the Cu-MOF nanozyme for colorimetric sensing but also enabled its use as an underlying backbone to support electroanalysis. Based on the recognition of nitrite through a highly specific diazo reaction between nitrite and oxTMB, the addition of nitrite caused the colorimetric sensing solution to change color from blue to green, which allowed for the colorimetric sensing of nitrite with a limit of detection (LOD) of 8.5 × 10-6 mol L-1. Meanwhile, the Cu-MOF/EGP electrochemical platform was employed for ratiometric detection of nitrite based on the electrochemical oxidation of nitrite and TMB. Compared with the colorimetric mode, the electrochemical mode possessed higher sensitivity with a LOD of 5.4 × 10-7 mol L-1, indicating the high sensitivity and accuracy of the proposed dual-mode sensing strategy. Furthermore, the determination of nitrite in different pickled food samples is demonstrated.

Unraveling the Possibilities: Recent Progress in DNA Biosensing

Due to the advantages of its numerous modification sites, predictable structure, high thermal stability, and excellent biocompatibility, DNA is the ideal choice as a key component of biosensors. DNA biosensors offer significant advantages over existing bioanalytical techniques, addressing limitations in sensitivity, selectivity, and limit of detection. Consequently, they have attracted significant attention from researchers worldwide. Here, we exemplify four foundational categories of functional nucleic acids: aptamers, DNAzymes, i-motifs, and G-quadruplexes, from the perspective of the structure-driven functionality in constructing DNA biosensors. Furthermore, we provide a concise overview of the design and detection mechanisms employed in these DNA biosensors. Noteworthy advantages of DNA as a sensor component, including its programmable structure, reaction predictility, exceptional specificity, excellent sensitivity, and thermal stability, are highlighted. These characteristics contribute to the efficacy and reliability of DNA biosensors. Despite their great potential, challenges remain for the successful application of DNA biosensors, spanning storage and detection conditions, as well as associated costs. To overcome these limitations, we propose potential strategies that can be implemented to solve these issues. By offering these insights, we aim to inspire subsequent researchers in related fields.

A Reaction-Based Optical Fingerprinting Strategy for the Recognition of Fat-Soluble Samples: Discrimination of Motor Oils

Optical "fingerprints" are widely used for chemometrics-assisted recognition of samples of different types. An emerging trend in this area is the transition from obtaining "static" spectral data to reactions analyzed over time. Indicator reactions are usually carried out in aqueous solutions; in this study, we developed reactions that proceed in an organic solvent, thereby making it possible to recognize fat-soluble samples. In this capacity, we used 5W40, 10W40, and 5W30 motor oils from four manufacturers, with six samples in total. The procedure involved mixing a dye, sample, and reagents (HNO3, HCl, or tert-butyl hydroperoxide) in an ethanolic solution in a 96-well plate and measuring absorbance or near-infrared fluorescence intensity every several minutes for 20-55 min. The obtained photographic images were processed by linear discriminant analysis (LDA) and the k-nearest neighbors algorithm (kNN). Discrimination accuracy was evaluated by a validation procedure. A reaction of oxidation of a dye by nitric acid allowed us to recognize all six samples with 100% accuracy for LDA. Merging of data from the four reactions that did not provide complete discrimination ensured an accuracy of 93% for kNN. The newly developed indicator systems have good prospects for the discrimination of other fat-soluble samples. Overall, the results confirm the viability of the kinetics-based discrimination strategy.

Multiplex Detection of Biogenic Amines for Meat Freshness Monitoring Using Nanoplasmonic Colorimetric Sensor Array

Biogenic amines (BAs) were presented as significant markers for the evaluation of the spoilage of meat and meat products. In this work, a colorimetric sensor array was developed for the discrimination and detection of spermine (SP), spermidine (SD), histamine (HS), and tryptamine (TP) as important BAs in food assessment. For this aim, two important spherical plasmonic nanoparticles, namely gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs), were utilized as the sensing elements of the probes. The cross-reactive interaction of the target biogenic amines and the plasmonic nanoparticles caused the aggregation-induced UV-Vis spectra changes, which were accompanied by visual color variation in the solution. The collected responses were analyzed by principal component analysis-linear discrimination analysis (PCA-LDA) to classify the four BAs. This colorimetric sensor array can also discriminate between the individual BAs and their mixture accurately. Partial least squares regression (PLS-R) was also utilized for quantitative analysis of the BAs. The wide linear concentration ranges of 0.1-10.0 µM for the four BAs and desirable figures of merits (FOMs) showed the potential of the developed sensor for quantitative detection of the BAs. Finally, the practical ability of the developed probe was studied by the determination of the BAs in the meat samples, which successfully proved the potential of the colorimetric sensor array in a food sample.

Plasmonic nanoparticle's anti-aggregation application in sensor development for water and wastewater analysis

Colorimetric sensors have emerged as a powerful tool in the detection of water pollutants. Plasmonic nanoparticles use localized surface plasmon resonance (LSPR)-based colorimetric sensing. LSPR-based sensing can be accomplished through different strategies such as etching, growth, aggregation, and anti-aggregation. Based on these strategies, various sensors have been developed. This review focuses on the newly developed anti-aggregation-based strategy of plasmonic nanoparticles. Sensors based on this strategy have attracted increasing interest because of their exciting properties of high sensitivity, selectivity, and applicability. This review highlights LSPR-based anti-aggregation sensors, their classification, and role of plasmonic nanoparticles in these sensors for the detection of water pollutants. The anti-aggregation based sensing of major water pollutants such as heavy metal ions, anions, and small organic molecules has been summarized herein. This review also provides some personal insights into current challenges associated with anti-aggregation strategy of LSPR-based colorimetric sensors and proposes future research directions.

Gold film effect on temperature compensation of a POF sensor with different structures

In this paper, temperature compensation of plastic optical fiber (POF) is studied and gold absorbability is utilized. Gold film is modified on the surface of POF by magnetron sputtering. The temperature output characteristics of different structures such as ordinary (POF-N), side-polished (POF-SP), U-shaped (POF-U), and narrow groove structure (POF-NGS) are tested, and the effects of gold film thickness, polishing area, and sputtering sequence on the temperature output characteristics are also investigated. The power change of the sensor at different temperatures is recorded. The experimental results show that when the temperature is between 25°C and 50°C and the sputtering gold film thickness is 50 nm, the temperature stabilities of POF-N, POF-U, POF-SP, and POF-NGS are 1.02 µW/°C, 0.77 µW/°C, 0.18 µW/°C, and 0.35 µW/°C, respectively. The compensation effect is enhanced as the gold film thickness increases. When the thickness is 100 nm, the temperature stability of POF-NGS is 0.06 µW/°C. The proposed temperature compensation method is competitive and straightforward.

A novel single-particle multiple-signal sensor array combined with multidimensional data mining for the detection of tricarboxylic acid cycle metabolites and discrimination of cells

Tricarboxylic acid (TCA) metabolites in cancer cells show a marked difference from those in normal cells. Herein, we report a single-particle multiple-signal lanthanide/europium-based metal-organic framework (Tb/Eu MOF) sensor array for the detection of TCA metabolites and discrimination of cancer cells. In the presence of TCA metabolite, 6 characteristic peaks of Tb/Eu MOF showed dramatic changes due to host-guest interactions, allowing sensor array-based qualitative and quantitative detection to be performed. In the qualitative detection ability test, 18 TCA metabolites at 4 concentrations (50 μM, 100 μM, 200 μM, 300 μM) were accurately discriminated by the sensor array via linear discriminant analysis (LDA). Significantly, these 4 concentrations include the clinical detection criteria for most TCA metabolites. In the quantitative detection ability test, a good linear relationship between Euclidean distances and the concentrations of L-valine (Val) could be obtained in the range of 50 to 500 μM (R² = 0.9755). On this basis, the provided method was successfully applied for the classification of 2 normal cells and 5 cancer cells via principal components analysis (PCA), LDA and a radial basis function neural network (RBFN). What's more, by verifying the weight coefficient of each point, detection and discrimination results are proved as a trustworthy balanced evaluation of multiple factors. Depending on precise data processing, the experimental operation was simplified on the premise of ensuring accuracy, so our method is a meaningful exploration for array design.

The Role of Nano-Sensors in Breath Analysis for Early and Non-Invasive Disease Diagnosis

Early-stage, precise disease diagnosis and treatment has been a crucial topic of scientific discussion since time immemorial. When these factors are combined with experience and scientific knowledge, they can benefit not only the patient, but also, by extension, the entire health system. The development of rapidly growing novel technologies allows for accurate diagnosis and treatment of disease. Nanomedicine can contribute to exhaled breath analysis (EBA) for disease diagnosis, providing nanomaterials and improving sensing performance and detection sensitivity. Through EBA, gas-based nano-sensors might be applied for the detection of various essential diseases, since some of their metabolic products are detectable and measurable in the exhaled breath. The design and development of innovative nanomaterial-based sensor devices for the detection of specific biomarkers in breath samples has emerged as a promising research field for the non-invasive accurate diagnosis of several diseases. EBA would be an inexpensive and widely available commercial tool that could also be used as a disease self-test kit. Thus, it could guide patients to the proper specialty, bypassing those expensive tests, resulting, hence, in earlier diagnosis, treatment, and thus a better quality of life. In this review, some of the most prevalent types of sensors used in breath-sample analysis are presented in parallel with the common diseases that might be diagnosed through EBA, highlighting the impact of incorporating new technological achievements in the clinical routine.

Identification of Proteins Using Supramolecular Gold Nanoparticle-Dye Sensor Arrays

The rapid detection of proteins is very important in the early diagnosis of diseases. Gold nanoparticles (AuNPs) can be engineered to bind biomolecules efficiently and differentially. Cross-reactive sensor arrays have high sensitivity for sensing proteins using differential interactions between sensor elements and bioanalytes. A new sensor array was fabricated using surface-charged AuNPs with dyes supramolecularly encapsulated into the AuNP monolayer. The fluorescence of dyes is partially quenched by the AuNPs and can be restored or further quenched due to the differential interactions between AuNPs with proteins. This sensing system enables the discrimination of proteins in both buffer and human serum, providing a potential tool for real-world disease diagnostics.

Colorimetric detection of mercury (Hg2+) using UV-vis spectroscopy and digital image analysis based on gold nanoparticles functionalized with bromelain enzyme

A very sensitive and selective colorimetric biosensor for the measurement of mercury ion (Hg2+) in environmental samples has been developed using functionalized gold nanoparticles with bromelain enzyme (brn-AuNPs). This work has shown that Hg2+ measurement based on spectrophotometer and digital image analysis is a very innovative and successful method for providing an effective preliminary system and has promise for the future of water quality biomonitoring. Response Surface Methodology (RSM), a Box-Behnken design-based technique, was used to identify the optimum levels of functionalization of bromelain to AuNPs. The created model's validity was confirmed, and statistical analysis revealed that the ideal functionalize conditions were 1 mM of AuNPs, functionalize with 0.59 mM bromelain concentration on 14 ℃ temperature and 72 h incubation time. The lowest colorimetric detection concentration (LOD) of brn-AuNPs of Hg2+ was 0.0092 ppm and 0.011 ppm for spectrophotometer and digital image analysis. As shown, digital image analysis had advantages based on the LOD result comparable to UV-VIS spectrophotometer. The practical application of the brn-AuNPs sensing was proven with mercury determination in water samples. The present study developed a robust sensor, which successfully implemented in a compact portable sensor kit, turning this sensor into a very potent tool for the development water quality biomonitoring system of Hg2+ application.

Carbocyanine-Based Optical Sensor Array for the Discrimination of Proteins and Rennet Samples Using Hypochlorite Oxidation

Optical sensor arrays are widely used in obtaining fingerprints of samples, allowing for solutions of recognition and identification problems. An approach to extending the functionality of the sensor arrays is using a kinetic factor by conducting indicator reactions that proceed at measurable rates. In this study, we propose a method for the discrimination of proteins based on their oxidation by sodium hypochlorite with the formation of the products, which, in turn, feature oxidation properties. As reducing agents to visualize these products, carbocyanine dyes IR-783 and Cy5.5-COOH are added to the reaction mixture at pH 5.3, and different spectral characteristics are registered every several minutes (absorbance in the visible region and fluorescence under excitation by UV (254 and 365 nm) and red light). The intensities of the photographic images of the 96-well plate are processed by principal component analysis (PCA) and linear discriminant analysis (LDA). Six model proteins (bovine and human serum albumins, γ-globulin, lysozyme, pepsin, and proteinase K) and 10 rennet samples (mixtures of chymosin and pepsin from different manufacturers) are recognized by the proposed method. The method is rapid and simple and uses only commercially available reagents.

Gold Nanoparticles as Exquisite Colorimetric Transducers for Water Pollutant Detection

Gold nanoparticles (AuNPs) are useful nanomaterials as transducers for colorimetric sensors because of their high extinction coefficient and ability to change color depending on aggregation status. Therefore, over the past few decades, AuNP-based colorimetric sensors have been widely applied in several environmental and biological applications, including the detection of water pollutants. According to various studies, water pollutants are classified into heavy metals or cationic metal ions, toxins, and pesticides. Notably, many researchers have been interested in AuNP that detect water pollutants with high sensitivity and selectivity, while offering no adverse environmental issues in terms of AuNP use. This review provides a representative overview of AuNP-based colorimetric sensors for detecting several water pollutants. In particular, we emphasize the advantages of AuNP as colorimetric transducers for water pollutant detection in terms of their low toxicity, high stability, facile processability, and unique optical properties. Next, we discuss the status quo and future prospects of AuNP-based colorimetric sensors for the detection of water pollutants. We believe that this review will promote research and development of AuNP as next-generation colorimetric transducers for water pollutant detection.

Chrono-colorimetric sensor array for detection and discrimination of halide ions using an all-in-one plasmonic sensor element

Most nanoparticle based colorimetric sensor array utilize several sensor elements and static response for discrimination of target analytes. This approach can be complicated and costly to synthesize or functionalize different nanoparticles for providing wide color variation. Herein, triangular silver nanoparticles (TSNPs) were used to develop a colorimetric sensor array by time-dimension responses. The principle of this sensor array is based on the diverse etching process of TSNPs in the presence of three halide ions, including bromide (Br^-), iodide (I^-) and chloride (Cl^-). Various etchings of TSNPs induced color changes at different reaction time intervals, which produced a colorimetric pattern for each ion. Therefore, using time dependent etching responses of TSNPs as a single sensing component can produce a wide color variation which can be distinguished by naked eyes. The colorimetric responses of TSNPs upon the addition of different concentrations of halide ions have been analyzed by PLS regression (PLS-R) and PLS discriminant analysis (PLS-DA). The analytical figures of merit confirmed that the developed chrono-colorimetric TSNPs -based sensor array is successful in both the discrimination and quantitative detection of halide ions. At the final step, the three halide ions were accurately determined in a real water sample, which verified the potential of the developed sensor in a real sample.

Nanozyme-based dual-signal sensing system for colorimetric and photothermal detection of AChE activity in the blood of liver-injured mice

Acetylcholinesterase (AChE), a crucial enzyme related to liver function, is involved in numerous physiological processes such as neurotransmission and muscular contraction. The currently reported techniques for detecting AChE mainly rely on a single signal output, limiting their high-accuracy quantification. The few reported dual-signal assays are challenging to implement in dual-signal point-of-care testing (POCT) because of the need for large instruments, costly modifications, and trained operators. Herein, we report a colorimetric and photothermal dual-signal POCT sensing platform based on CeO₂-TMB (3,3',5,5'-tetramethylbenzidine) for the visualization of AChE activity in liver-injured mice. The method compensates for the false positives of a single signal and realizes the rapid, low-cost portable detection of AChE. More importantly, the CeO₂-TMB sensing platform enables the diagnosis of liver injury and provides an effective tool for studying liver disease in basic medicine and clinical applications. Rapid colorimetric and photothermal biosensor for sensitive detection of acetylcholinesterase (I) and acetylcholinesterase levels in mouse serum (II).

Optical sensor arrays for the detection and discrimination of natural products

Covering: up to the end of 2022Natural products (NPs) have found uses in medicine, food, cosmetics, materials science, environmental protection, and other fields related to our life. Their beneficial properties along with potential toxicities make the detection and discrimination of NPs crucial for their applications. Owing to the merits of low cost and simple operation, optical sensor arrays, including colorimetric and fluorometric sensor arrays, have been widely applied in the detection of small molecule NPs and discrimination of structurally similar small molecule NPs or complex mixtures of NPs. This review provides a brief introduction to the optical sensor array and focuses on its progress toward the detection and discrimination of NPs. We summarized the design principle of sensor arrays toward various NPs (i.e., saccharides and polyhydroxy compounds, organic acids, flavonoids, organic sulfur compounds, amines, amino acids, and saponins) based on their functional groups and characteristic chemical properties, along with representative examples. Moreover, the challenges and potential directions for further research of optical sensor arrays for NPs are proposed.

Cysteamine-decorated gold nanoparticles for plasmon-based colorimetric on-site sensors for detecting cyanide ions using the smart-phone color ratio and for catalytic reduction of 4-nitrophenol

In this paper, we have reported the cyanide ions (CN^-) sensing in environmental water samples using cysteamine-capped gold nanoparticles (Cyst-AuNPs) by spectrophotometric, colorimetric, and smartphone-based RGB color detection. The surface plasmon resonance shift at around 525 nm for the Cyst-AuNPs could be used to detect quantitatively the amounts of CN^- with concomitant alteration of their color from wine red to purple visualized by the naked eye. For the first time, the Cyst-AuNPs-based visual sensing of CN^- was performed using smartphone-based detection with its detection limit of 159 × 10^-9 M, ten times lower than that of the highest tolerance level (2 × 10^-6 M) permitted by the world health organization. The Cyst-AuNPs displayed excellent specificity for detecting the concentration of 30 × 10^-6 M even amid the presence of other interfering inorganic anions with their concentrations about five times higher than it. Environmental real water samples were used to arrange the three different CN^- concentrations for plasmon-based colorimetric detection and smartphone-based method. Additionally, the catalytic performance of Cyst-AuNPs was demonstrated for the fast catalytic conversion of hazardous 4-nitrophenol (selected environmental contaminant) to the analogous amino aromatic compounds. A chemical kinetic study showed the conversion rate to be estimated as 1.65 × 10^-2 s^-1. Cyst-AuNPs can find an application in colorimetric sensing of CN^- while being able to be utilized as a catalytic nanomaterial for ecological remedies associated with health care.

Conjugation of cysteamine functionalized nanodiamond to gold nanoparticles for pH enhanced colorimetric detection of Cr3+ ions demonstrated by real water sample analysis

A cysteamine functionalized nanodiamond (NDC) was conjugated to gold nanoparticles (AuNPs) to deliver NDC@AuNPs and utilized in enhanced colorimetric detection of Cr³⁺ at pH 6 environment. The conjugation was validated using FTIR, TEM, PXRD, DLS, and zeta potential investigations. At pH 6, superior sensory response of NDC@AuNPs to Cr³⁺ than that of other ions was validated by UV-vis spectroscopy and colorimetric photographs. Results from UV-vis titrations displayed a linear regression from 0.01 to 0.4 µM with a LOD of 0.236 ± 0.005 nM. The particle aggregation, size variations, potential changes, and binding modes are investigated using TEM, DLS, and FTIR techniques to explore the underlying mechanisms. By adding the EDTA, sensory response is reversible up to 4 cycles. Finally, spiked real water experiments show improved sensing of Cr³⁺ at pH 6 via the observed recovery between 96 and 110 %, which is in good agreement with the ICP-mass data.

Fluorescence Detection of Trace Disinfection Byproducts by Ag Nanoprism-Modulated Lanthanide MOFs

Disinfection byproducts (DBPs), as an emerging water pollutant, present increasing concern and risk in public health and water safety. Due to their low concentration levels and inherent similarity in molecular structures, sensitive and accurate determination of DBPs is still a challenge especially for onsite or online detection. Herein, a self-regulated fluorescent probe based on the Ag nanoprism-modified lanthanide metal-organic framework (AgNPR@EuMOF) is designed for trichloroacetic acid (TCAA) detection. The EuMOF is constructed with Eu as the metal node and 5-boronoisophthalic acid as the ligand. By introducing sulfhydryl groups into EuMOF, AgNPR can be anchored on the EuMOF surface through Ag-S bonds, enabling the synthesis of stable AgNPR@EuMOF composites. During the sensing process, the triangle AgNPR will react with the organic halogen molecule, accomplished with the blue shift of surface plasmon resonance absorption peak and the significant change in the fluorescence of EuMOF. This probe can detect TCAA in a wide concentration range (0.1-40 μM) with high sensitivity and specificity. The density functional theory calculation on binding energies between DBPs and AgNPR suggests that TCAA has the largest interaction ability with AgNPR than other DBPs. Moreover, the detection of TCAA in real tap water and swimming pool water is also demonstrated with high accuracy. The reported AgNPR@EuMOF represents one of the pioneer fluorescence probes in DBP detection, which holds great promise for onsite or online analysis of trace DBPs in water.